Any financial institution that invests in its indirect lending program understands how difficult it can be to separate itself from the competition. Besides offering the best rates or dealer incentives, the most successful lenders are often the ones that provide the best service. This often means delivering fast and accurate decisions while dealers are trying to close a sale. That’s why it’s important for financial institutions to rely on loan software technology that pushes them forward rather than holding them back. Here are a few best practices to consider when evaluating if a loan origination system is the right fit for your financial institution's goals and strategies:

Have you filled out your bracket yet? If not, you better get on it soon since the big dance starts in just over an hour. It’s always interesting how so many people have unique strategies when deciding on the teams that will advance and eventually be crowned champions of college hoops. Some people have watched so many games this season that they can make educated decisions. While others, like me, find other less analytical ways to decide since they haven’t seen at least half of the teams actually play. Almost everyone knows or has heard a story of someone who won a pool because of picking something like their favorite mascots or colors. The point is that there is no single method or formula that leads to victory. While some people have won with crazy strategies, it’s best go with what works best for you. For digital lending success, it sort of like that – although the stakes are much higher. From the online or mobile application process to the decisoning, workflow and funding processes, financial institutions everywhere are still searching for the right strategy to survive and advance among today’s fierce competition. That’s why we’re here to help. This week’s blog post features three more of the most important best practices every financial institution needs to consider when evaluating technology and processes:

Following last week’s blog post regarding silo analytics, we’re going to take it one step further this week. As opposed to last week’s topic, which centered on using a single piece of (or incomplete) information to represent a holistic view of the consumer, silo analytics also refers to decentralized or fragmented process for analytics. In this example, each department within the same organization (such as marketing, credit risk, acquisitions and collections) often rebuilds its analytic infrastructure from data gathering to the creation of analytic attributes rather than partnering across divisions to improve the speed to implementation. For the second part of this two-part series, this week's blog post will take a deeper look at what institutions can do to avoid such a decentralized and fragmented process.

Analytics can be an extremely profitable investment – assuming efficiency and completion. Financial institutions, whether they handle it in house or turn things over to a trusted provider, need to know if they’re victims of leveraging or being served silo analytics to dictate their credit decisioning.